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Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study
Epilepsia
Swansea University Authors:
Beata Fonferko-Shadrach, Arron Lacey, Huw Strafford, Carys Jones, Ashley Akbari , Ronan Lyons
, David Ford
, Simon Ellwood-Thompson, Kerina Jones
, Owen Pickrell
-
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© 2023 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy. Distributed under the terms of a Creative Commons Attribution Non Commercial 4.0 License (CC BY-NC 4.0).
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DOI (Published version): 10.1111/epi.17766
Abstract
Objective: This study was undertaken to develop a novel pathway linking genetic data with routinely collected data for people with epilepsy, and to analyze the influence of rare, deleterious genetic variants on epilepsy outcomes. Methods: We linked whole-exome sequencing (WES) data with routinely co...
Published in: | Epilepsia |
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ISSN: | 0013-9580 1528-1167 |
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Wiley
2023
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<?xml version="1.0" encoding="utf-8"?><rfc1807 xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:xsd="http://www.w3.org/2001/XMLSchema"><bib-version>v2</bib-version><id>64175</id><entry>2023-08-30</entry><title>Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study</title><swanseaauthors><author><sid>7d3f1e80939f2b8fab6a16b5ec6ac845</sid><firstname>Beata</firstname><surname>Fonferko-Shadrach</surname><name>Beata Fonferko-Shadrach</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>b69d245574e754d2637cc9e76379fe11</sid><firstname>Arron</firstname><surname>Lacey</surname><name>Arron Lacey</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>a6389fc6d4d18e7b67033ee04b381e43</sid><firstname>Huw</firstname><surname>Strafford</surname><name>Huw Strafford</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>76dda5f486b0236c893f46dfb9fa2cd0</sid><firstname>Carys</firstname><surname>Jones</surname><name>Carys Jones</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>aa1b025ec0243f708bb5eb0a93d6fb52</sid><ORCID>0000-0003-0814-0801</ORCID><firstname>Ashley</firstname><surname>Akbari</surname><name>Ashley Akbari</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>83efcf2a9dfcf8b55586999d3d152ac6</sid><ORCID>0000-0001-5225-000X</ORCID><firstname>Ronan</firstname><surname>Lyons</surname><name>Ronan Lyons</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>52fc0c473b0da1b7218d87f9fc68a3e6</sid><ORCID>0000-0001-6551-721X</ORCID><firstname>David</firstname><surname>Ford</surname><name>David Ford</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>6498256ca5bc432bd9626503f1019113</sid><firstname>Simon</firstname><surname>Ellwood-Thompson</surname><name>Simon Ellwood-Thompson</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>c13b3cd0a6f8cbac2e461b54b3cdd839</sid><ORCID>0000-0001-8164-3718</ORCID><firstname>Kerina</firstname><surname>Jones</surname><name>Kerina Jones</name><active>true</active><ethesisStudent>false</ethesisStudent></author><author><sid>1c3044b5ff7a6552ff5e8c9e3901c807</sid><ORCID>0000-0003-4396-5657</ORCID><firstname>Owen</firstname><surname>Pickrell</surname><name>Owen Pickrell</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2023-08-30</date><deptcode>HDAT</deptcode><abstract>Objective: This study was undertaken to develop a novel pathway linking genetic data with routinely collected data for people with epilepsy, and to analyze the influence of rare, deleterious genetic variants on epilepsy outcomes. Methods: We linked whole-exome sequencing (WES) data with routinely collected primary and secondary care data and natural language processing (NLP)-derived seizure frequency information for people with epilepsy within the Secure Anonymised Information Linkage Databank. The study participants were adults who had consented to participate in the Swansea Neurology Biobank, Wales, between 2016 and 2018. DNA sequencing was carried out as part of the Epi25 collaboration. For each individual, we calculated the total number and cumulative burden of rare and predicted deleterious genetic variants and the total of rare and deleterious variants in epilepsy and drug metabolism genes. We compared these measures with the following outcomes: (1) no unscheduled hospital admissions versus unscheduled admissions for epilepsy, (2) antiseizure medication (ASM) monotherapy versus polytherapy, and (3) at least 1 year of seizure freedom versus <1 year of seizure freedom. Results: We linked genetic data for 107 individuals with epilepsy (52% female) to electronic health records. Twenty-six percent had unscheduled hospital admissions, and 70% were prescribed ASM polytherapy. Seizure frequency information was linked for 100 individuals, and 10 were seizure-free. There was no significant difference between the outcome groups in terms of the exome-wide and gene-based burden of rare and deleterious genetic variants. Significance: We successfully uploaded, annotated, and linked genetic sequence data and NLP-derived seizure frequency data to anonymized health care records in this proof-of-concept study. We did not detect a genetic influence on real-world epilepsy outcomes, but our study was limited by a small sample size. Future studies will require larger (WES) data to establish genetic variant contribution to epilepsy outcomes.</abstract><type>Journal Article</type><journal>Epilepsia</journal><volume/><journalNumber/><paginationStart/><paginationEnd/><publisher>Wiley</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0013-9580</issnPrint><issnElectronic>1528-1167</issnElectronic><keywords>Antiseizure medication, genetic variant burden, natural language processing, seizure frequency, unscheduled admission</keywords><publishedDay>15</publishedDay><publishedMonth>9</publishedMonth><publishedYear>2023</publishedYear><publishedDate>2023-09-15</publishedDate><doi>10.1111/epi.17766</doi><url>http://dx.doi.org/10.1111/epi.17766</url><notes/><college>COLLEGE NANME</college><department>Health Data Science</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>HDAT</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders>This work was supported by staff funded as part of the Wales Gene Park, an infrastructure support group funded by the Welsh Government through Health and Care Research Wales. The views expressed are those of the authors and not necessarily those of Health and Care Research Wales or the Welsh Government. We thank and acknowledge our colleagues in the Broad Institute and the Epi25 collaborative (http://epi-25.org/). Epi25 regards this work as a local secondary study limited to repatriated WES data. No other submitting Epi25 sites were included due to the limited study access to Wales National Health Service health care data. This study used anonymized data held in the Secure Anonymised Information Linkage Databank. We would like to acknowledge all the data providers who make anonymized data available for research. Open access publishing facilitated by The University of Sydney, as part of the Wiley - The University of Sydney agreement via the Council of Australian University Librarians.</funders><projectreference/><lastEdited>2023-09-26T11:03:08.9490214</lastEdited><Created>2023-08-30T14:37:33.6496623</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Beata</firstname><surname>Fonferko-Shadrach</surname><order>1</order></author><author><firstname>Arron</firstname><surname>Lacey</surname><order>2</order></author><author><firstname>Huw</firstname><surname>Strafford</surname><order>3</order></author><author><firstname>Carys</firstname><surname>Jones</surname><order>4</order></author><author><firstname>Mark</firstname><surname>Baker</surname><order>5</order></author><author><firstname>Robert</firstname><surname>Powell</surname><order>6</order></author><author><firstname>Ashley</firstname><surname>Akbari</surname><orcid>0000-0003-0814-0801</orcid><order>7</order></author><author><firstname>Ronan</firstname><surname>Lyons</surname><orcid>0000-0001-5225-000X</orcid><order>8</order></author><author><firstname>David</firstname><surname>Ford</surname><orcid>0000-0001-6551-721X</orcid><order>9</order></author><author><firstname>Simon</firstname><surname>Ellwood-Thompson</surname><order>10</order></author><author><firstname>Kerina</firstname><surname>Jones</surname><orcid>0000-0001-8164-3718</orcid><order>11</order></author><author><firstname>Seo‐Kyung</firstname><surname>Chung</surname><order>12</order></author><author><firstname>Owen</firstname><surname>Pickrell</surname><orcid>0000-0003-4396-5657</orcid><order>13</order></author><author><firstname>Mark I.</firstname><surname>Rees</surname><order>14</order></author></authors><documents><document><filename>64175__28636__8e20f2d917bc4e4fad2db5062e2ac9ce.pdf</filename><originalFilename>64175.VOR.pdf</originalFilename><uploaded>2023-09-26T11:00:16.3236247</uploaded><type>Output</type><contentLength>2301431</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>© 2023 The Authors. 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spelling |
v2 64175 2023-08-30 Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study 7d3f1e80939f2b8fab6a16b5ec6ac845 Beata Fonferko-Shadrach Beata Fonferko-Shadrach true false b69d245574e754d2637cc9e76379fe11 Arron Lacey Arron Lacey true false a6389fc6d4d18e7b67033ee04b381e43 Huw Strafford Huw Strafford true false 76dda5f486b0236c893f46dfb9fa2cd0 Carys Jones Carys Jones true false aa1b025ec0243f708bb5eb0a93d6fb52 0000-0003-0814-0801 Ashley Akbari Ashley Akbari true false 83efcf2a9dfcf8b55586999d3d152ac6 0000-0001-5225-000X Ronan Lyons Ronan Lyons true false 52fc0c473b0da1b7218d87f9fc68a3e6 0000-0001-6551-721X David Ford David Ford true false 6498256ca5bc432bd9626503f1019113 Simon Ellwood-Thompson Simon Ellwood-Thompson true false c13b3cd0a6f8cbac2e461b54b3cdd839 0000-0001-8164-3718 Kerina Jones Kerina Jones true false 1c3044b5ff7a6552ff5e8c9e3901c807 0000-0003-4396-5657 Owen Pickrell Owen Pickrell true false 2023-08-30 HDAT Objective: This study was undertaken to develop a novel pathway linking genetic data with routinely collected data for people with epilepsy, and to analyze the influence of rare, deleterious genetic variants on epilepsy outcomes. Methods: We linked whole-exome sequencing (WES) data with routinely collected primary and secondary care data and natural language processing (NLP)-derived seizure frequency information for people with epilepsy within the Secure Anonymised Information Linkage Databank. The study participants were adults who had consented to participate in the Swansea Neurology Biobank, Wales, between 2016 and 2018. DNA sequencing was carried out as part of the Epi25 collaboration. For each individual, we calculated the total number and cumulative burden of rare and predicted deleterious genetic variants and the total of rare and deleterious variants in epilepsy and drug metabolism genes. We compared these measures with the following outcomes: (1) no unscheduled hospital admissions versus unscheduled admissions for epilepsy, (2) antiseizure medication (ASM) monotherapy versus polytherapy, and (3) at least 1 year of seizure freedom versus <1 year of seizure freedom. Results: We linked genetic data for 107 individuals with epilepsy (52% female) to electronic health records. Twenty-six percent had unscheduled hospital admissions, and 70% were prescribed ASM polytherapy. Seizure frequency information was linked for 100 individuals, and 10 were seizure-free. There was no significant difference between the outcome groups in terms of the exome-wide and gene-based burden of rare and deleterious genetic variants. Significance: We successfully uploaded, annotated, and linked genetic sequence data and NLP-derived seizure frequency data to anonymized health care records in this proof-of-concept study. We did not detect a genetic influence on real-world epilepsy outcomes, but our study was limited by a small sample size. Future studies will require larger (WES) data to establish genetic variant contribution to epilepsy outcomes. Journal Article Epilepsia Wiley 0013-9580 1528-1167 Antiseizure medication, genetic variant burden, natural language processing, seizure frequency, unscheduled admission 15 9 2023 2023-09-15 10.1111/epi.17766 http://dx.doi.org/10.1111/epi.17766 COLLEGE NANME Health Data Science COLLEGE CODE HDAT Swansea University Another institution paid the OA fee This work was supported by staff funded as part of the Wales Gene Park, an infrastructure support group funded by the Welsh Government through Health and Care Research Wales. The views expressed are those of the authors and not necessarily those of Health and Care Research Wales or the Welsh Government. We thank and acknowledge our colleagues in the Broad Institute and the Epi25 collaborative (http://epi-25.org/). Epi25 regards this work as a local secondary study limited to repatriated WES data. No other submitting Epi25 sites were included due to the limited study access to Wales National Health Service health care data. This study used anonymized data held in the Secure Anonymised Information Linkage Databank. We would like to acknowledge all the data providers who make anonymized data available for research. Open access publishing facilitated by The University of Sydney, as part of the Wiley - The University of Sydney agreement via the Council of Australian University Librarians. 2023-09-26T11:03:08.9490214 2023-08-30T14:37:33.6496623 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Beata Fonferko-Shadrach 1 Arron Lacey 2 Huw Strafford 3 Carys Jones 4 Mark Baker 5 Robert Powell 6 Ashley Akbari 0000-0003-0814-0801 7 Ronan Lyons 0000-0001-5225-000X 8 David Ford 0000-0001-6551-721X 9 Simon Ellwood-Thompson 10 Kerina Jones 0000-0001-8164-3718 11 Seo‐Kyung Chung 12 Owen Pickrell 0000-0003-4396-5657 13 Mark I. Rees 14 64175__28636__8e20f2d917bc4e4fad2db5062e2ac9ce.pdf 64175.VOR.pdf 2023-09-26T11:00:16.3236247 Output 2301431 application/pdf Version of Record true © 2023 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy. Distributed under the terms of a Creative Commons Attribution Non Commercial 4.0 License (CC BY-NC 4.0). true eng https://creativecommons.org/licenses/by-nc/4.0/ |
title |
Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study |
spellingShingle |
Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study Beata Fonferko-Shadrach Arron Lacey Huw Strafford Carys Jones Ashley Akbari Ronan Lyons David Ford Simon Ellwood-Thompson Kerina Jones Owen Pickrell |
title_short |
Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study |
title_full |
Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study |
title_fullStr |
Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study |
title_full_unstemmed |
Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study |
title_sort |
Genetic influences on epilepsy outcomes: a whole‐exome sequencing and healthcare records data linkage study |
author_id_str_mv |
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7d3f1e80939f2b8fab6a16b5ec6ac845_***_Beata Fonferko-Shadrach b69d245574e754d2637cc9e76379fe11_***_Arron Lacey a6389fc6d4d18e7b67033ee04b381e43_***_Huw Strafford 76dda5f486b0236c893f46dfb9fa2cd0_***_Carys Jones aa1b025ec0243f708bb5eb0a93d6fb52_***_Ashley Akbari 83efcf2a9dfcf8b55586999d3d152ac6_***_Ronan Lyons 52fc0c473b0da1b7218d87f9fc68a3e6_***_David Ford 6498256ca5bc432bd9626503f1019113_***_Simon Ellwood-Thompson c13b3cd0a6f8cbac2e461b54b3cdd839_***_Kerina Jones 1c3044b5ff7a6552ff5e8c9e3901c807_***_Owen Pickrell |
author |
Beata Fonferko-Shadrach Arron Lacey Huw Strafford Carys Jones Ashley Akbari Ronan Lyons David Ford Simon Ellwood-Thompson Kerina Jones Owen Pickrell |
author2 |
Beata Fonferko-Shadrach Arron Lacey Huw Strafford Carys Jones Mark Baker Robert Powell Ashley Akbari Ronan Lyons David Ford Simon Ellwood-Thompson Kerina Jones Seo‐Kyung Chung Owen Pickrell Mark I. Rees |
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Journal article |
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Epilepsia |
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2023 |
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Swansea University |
issn |
0013-9580 1528-1167 |
doi_str_mv |
10.1111/epi.17766 |
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Wiley |
college_str |
Faculty of Medicine, Health and Life Sciences |
hierarchytype |
|
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facultyofmedicinehealthandlifesciences |
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Faculty of Medicine, Health and Life Sciences |
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facultyofmedicinehealthandlifesciences |
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Faculty of Medicine, Health and Life Sciences |
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Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine |
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http://dx.doi.org/10.1111/epi.17766 |
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description |
Objective: This study was undertaken to develop a novel pathway linking genetic data with routinely collected data for people with epilepsy, and to analyze the influence of rare, deleterious genetic variants on epilepsy outcomes. Methods: We linked whole-exome sequencing (WES) data with routinely collected primary and secondary care data and natural language processing (NLP)-derived seizure frequency information for people with epilepsy within the Secure Anonymised Information Linkage Databank. The study participants were adults who had consented to participate in the Swansea Neurology Biobank, Wales, between 2016 and 2018. DNA sequencing was carried out as part of the Epi25 collaboration. For each individual, we calculated the total number and cumulative burden of rare and predicted deleterious genetic variants and the total of rare and deleterious variants in epilepsy and drug metabolism genes. We compared these measures with the following outcomes: (1) no unscheduled hospital admissions versus unscheduled admissions for epilepsy, (2) antiseizure medication (ASM) monotherapy versus polytherapy, and (3) at least 1 year of seizure freedom versus <1 year of seizure freedom. Results: We linked genetic data for 107 individuals with epilepsy (52% female) to electronic health records. Twenty-six percent had unscheduled hospital admissions, and 70% were prescribed ASM polytherapy. Seizure frequency information was linked for 100 individuals, and 10 were seizure-free. There was no significant difference between the outcome groups in terms of the exome-wide and gene-based burden of rare and deleterious genetic variants. Significance: We successfully uploaded, annotated, and linked genetic sequence data and NLP-derived seizure frequency data to anonymized health care records in this proof-of-concept study. We did not detect a genetic influence on real-world epilepsy outcomes, but our study was limited by a small sample size. Future studies will require larger (WES) data to establish genetic variant contribution to epilepsy outcomes. |
published_date |
2023-09-15T11:03:10Z |
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1778094010911424512 |
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11.021648 |